Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join our team to drive data analysis and machine learning in Private Equity.
- Company: We're a leading firm in Private Equity, focused on innovative investment strategies.
- Benefits: Enjoy a hybrid work model, competitive salary, bonuses, and great perks.
- Why this job: Be part of a dynamic investment team and make impactful decisions with data.
- Qualifications: Must have 3-4+ years in data roles, preferably in Private Equity, with Python and SQL skills.
- Other info: This role offers direct exposure to senior stakeholders and exciting projects.
The predicted salary is between 90000 - 210000 £ per year.
Job Description
Senior Data Scientist
London – Hybrid (4 days a week)
Up to £150,000 + bonus and benefits
This is a great opportunity for a Data Scientist to work in the Private Equity space, reporting directly into a Head of Data.
THE ROLE
In this role you will:
- Work on due diligence, reporting for investment teams in a data environment
- Build out and scale Machine Learning with Python and SQL
- Drive Data Visualisation with Tableau/Power BI
- Work on Cashflow predictive models to optimise investment decisions
- Be part of the front office investment team, working closely with senior stakeholders
Skills And Experience
- Candidates must have experience in Private Equity – preferably in a Data team
- Or experience in a strategy consultancy, ideally with a focus on PE projects
- MSc or BSc in a numerical or relevant field is preferred with 3-4+ years of experience
- Python and SQL experience is required
How To Apply
Please register your interest for this role by sending your CV to Kiran Ramasamy via the apply link on this page
#J-18808-Ljbffr
Senior Data Scientist - Private Equity employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - Private Equity
✨Tip Number 1
Make sure to highlight your experience in Private Equity or strategy consultancy during the interview. Be prepared to discuss specific projects you've worked on that relate to data analysis and investment strategies.
✨Tip Number 2
Familiarize yourself with the latest trends in Machine Learning and Data Visualization tools like Tableau and Power BI. Being able to discuss recent advancements or case studies can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the Private Equity space. Attend industry events or webinars where you can meet potential colleagues and learn more about the challenges they face, which can help you tailor your approach.
✨Tip Number 4
Prepare to demonstrate your technical skills in Python and SQL during the interview. You might be asked to solve a problem or analyze a dataset on the spot, so practice coding challenges related to data science.
We think you need these skills to ace Senior Data Scientist - Private Equity
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Private Equity and any relevant data projects. Emphasize your skills in Python, SQL, and data visualization tools like Tableau or Power BI.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the role of Senior Data Scientist in Private Equity. Mention your experience with due diligence, cashflow predictive models, and how you can contribute to the investment team.
Showcase Relevant Projects: Include specific examples of past projects where you utilized machine learning, data analysis, or worked closely with senior stakeholders. This will demonstrate your hands-on experience and ability to drive results.
Follow Application Instructions: Ensure you send your application through the provided link and address it to Kiran Ramasamy. Double-check that all documents are attached and formatted correctly before submitting.
How to prepare for a job interview at Harnham
✨Showcase Your Private Equity Knowledge
Make sure to highlight your experience in the Private Equity space during the interview. Be prepared to discuss specific projects you've worked on and how they relate to data science.
✨Demonstrate Technical Proficiency
Since Python and SQL are crucial for this role, be ready to discuss your technical skills in detail. You might even be asked to solve a problem or explain your approach to a data challenge.
✨Prepare for Stakeholder Interaction
As you'll be working closely with senior stakeholders, practice articulating complex data concepts in a way that's easy to understand. This will show that you can bridge the gap between data science and business needs.
✨Discuss Data Visualization Techniques
Be prepared to talk about your experience with data visualization tools like Tableau or Power BI. Share examples of how you've used these tools to drive insights and support investment decisions.
